ecgdig: dataset card and file manifest

README.md

@@ -0,0 +1,47 @@
+---
+pretty_name: ECG Image Digitization
+license: cc-by-4.0
+task_categories:
+- image-to-text
+- time-series-forecasting
+tags:
+- ecg
+- medical
+- signal-processing
+- image
+size_categories:
+- 1K<n<10K
+---
+
+# ECG Image Digitization
+
+Recover 12-lead ECG voltage time series from images of printed ECG pages. Each record is
+one 10 second 12-lead acquisition; training records carry nine renderings of the same
+printed page under different scan and photograph conditions.
+
+## Contents
+
+The data tree lives under `data/`, exactly as the benchmark environment presents it at
+`/app/ecgdig`. Its own description is at `data/README.md`.
+
+- 7074 files, 12821532396 bytes (11.9 GiB)
+- structure hash (sha256 over sorted `path\tsize` lines): `b476fd2dcfec31e3b18025da79d38d723cb1efd19e4ea99594d8c290b61a665b`
+- `data.manifest.tsv` at the repo root lists every file as `sha256  size  path`
+
+## Use
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download("Emulated-Inc/ecgdig", repo_type="dataset", revision="REVISION",
+                  local_dir="./ecgdig", allow_patterns="data/*")
+```
+
+Pin `revision` to a commit sha rather than a branch if you need reproducibility.
+
+## Provenance and licence
+
+Derived from the PhysioNet Digitization of ECG Images Kaggle competition
+(https://www.kaggle.com/competitions/physionet-ecg-image-digitization), whose data is
+released under CC BY 4.0. Attribution is required by that licence; please cite
+PhysioNet and the competition when using this dataset.